high performance computing on graphics processing units: hgpu.org

In this study, artificial compressibility method and virtual flux method were implemented on GPUs. Because GPUs are recognized as massively parallel computers, DP-LUR was employed as time integration method. In spite of slow convergence characteristics of DP-LUR, calculation by the coupling of DP-LUR and GPU is about 15 times faster in time than that of […]

Motivation: The importance of stochasticity in biological systems is becoming increasingly recognised and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU which exploits graphics processing units (GPUs) for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency […]

Several parallel architectures such as GPUs and the Cell processor have fast explicitly managed on-chip memories, in addition to slow off-chip memory. They also have very high computational power with multiple levels of parallelism. A significant challenge in programming these architectures is to effectively exploit the parallelism available in the architecture and manage the fast […]

Graphics hardware is advancing very fast and offers new possibilities to programmers. The new features can be used in scientific visualization to move calculations from the CPU to the graphics processing unit (GPU). This is useful especially when mixing CPU intense calculations with on the fly visualization of intermediate results. We present a method to […]

In this paper, we present an efficient Hierarchical Parallel Genetic Algorithm framework using Grid computing (GE-HPGA). The framework is developed using standard Grid technologies, and has two distinctive features: (1) an extended GridRPC API to conceal the high complexity of the Grid environment, and (2) a metascheduler for seamless resource discovery and selection. To assess […]

Accurately rendering an ellipsoid is a fundamental problem for virtual globes in GIS and aerospace applications where the Earth’s standard reference surface is non-spherical. The traditional approach of tessellating an ellipsoid into triangles and rendering via rasterization has several drawbacks [Miller and Gaskins 2009]. Geodetic grid tessellations oversample at the poles (2a), which leads to […]

We review the current state of data mining and machine learning in astronomy. ‘Data Mining’ can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding the potential to fully exploit the exponentially increasing amount of available data, promising […]

The massive computational power available in off-the shelf Graphics Processing Units (GPUs) can pave the way for its usage in general purpose applications. Current interfaces to program GPU operation are still oriented towards graphics processing. This paper is focused in disparities on those programming interfaces and proposes an extension to of the recently developed Caravela […]

This paper presents an acceleration method for tracking a bronchoscope based on image registration. This method tracks a bronchoscope by image registration between real bronchoscopic images and virtual ones derived from CT images. However, since the computation cost of image registration, especially generating virtual bronchoscopic (VB) images, is quite expensive, it is dificult to track […]

Biological sequence comparison is a very important operation in Bioinformatics. Even though there do exist exact methods to compare biological sequences, these methods are often neglected due to their quadratic time and space complexity. In order to accelerate these methods, many GPU algorithms were proposed in the literature. Nevertheless, all of them restrict the size […]

GPUs offer drastically different performance characteristics compared to traditional multicore architectures. To explore the tradeoffs exposed by this difference, we refactor MUMmer, a widely-used, highly-engineered bioinformatics application which has both CPU- and GPU-based implementations. We synthesize our experience as three high-level guidelines to design efficient GPU-based applications. First, minimizing the communication overheads is as important […]

Graphs are powerful data representations favored in many computational domains. Modern GPUs have recently shown promising results in accelerating computationally challenging graph problems but their performance suffers heavily when the graph structure is highly irregular, as most real-world graphs tend to be. In this study, we first observe that the poor performance is caused by […]